1. Open PHACTS 1.3 Release (2 701 602 484 triples)
Blue font indicates new data and new data sources available in 1.3

2. 1.3 Release Summary
Integration of WikiPathways to provide a series of pathway-based API calls
A refresh of ChEMBL to ChEMBL_16
Extension and better support for units and filtering of pharmacology data. Support for pChEMBL filtering
Ability to query hierarchy data in queries (GO, ChEBI, ChEMBL target, ENZYME)
All new chemistry processing using the Open PHACTS Chemistry registry and new chemistry "lenses" for flexible mapping
Further development of KNIME and Pipeline Pilot Nodes
Further development of our support portal at support.openphacts.org

3. Open PHACTS 1.3 Data Content

4. Open PHACTS 1.3 Supported Identifiers
We now support an increased range of public database identifiers for proteins and compounds.
Please see: openphacts.cs.man.ac.uk:9093/QueryExpander/mappingSet?lensUri=All
Home page: openphacts.cs.man.ac.uk for supported identifiers including:
HGNC Symbols
GeneOntology
ChEMBL ID
Ensembl
EntrezGene
and many more….

5. Details on new methods & data

6. Compound API Methods

7. Compound Info Data SMILES, InChI, InChIKey
logP, Hydrogen bond acceptor or donor, Rule of 5 violations, Polar surface area
Rotatable bonds, molecular weight, molecular formula, Freebase molecular weight
Biotransformation, description, protein binding, toxicity, melting point, drug name, drug type (approved, experimental, etc)
Compound name

8. Compound Info Data Sources
OPS chemical registration system (OCRS)
ChEMBL (ChEMBL_16)
molecule dataset triples
DrugBank
ConceptWiki (Sept 9, 2013 ChemSpider)

9. Compound Class Data Sources
ChEBI : Count, List, Compound Classifications
GeneOntology : Compound Classifications, Target Classification
ChEBML Targets: Target Classification ( triples)
ENZYME: Target Classification

10. Compound Pharmacology Data
Compound data:
Activity (type, value, units, comment),
pChEMBL, Assay (type, organism, description),
URIs (OCRS, ChEMBL, ConceptWiki, DrugBank), Drug type, Generic name, SMILES, InChI, InChIKey, molecular weight, Rule of 5, Literature (DOI, PMID)
Target data:
Name, organism
target component, target type

11. Compound Pharmacology Data Sources
OPS chemical registration system (OCRS)
ChEMBL
activity dataset triples
assay dataset triples
DrugBank ( triples)

12. Compound Class Pharmacology
Activity values for compounds from a given ChEBI compound class

13. Chemical Structure Mapping Methods

14. Chemical Structure Conversion and Search Data
Conversion of InChI, InChIKey, SMILES, to OCRS URIs
Chemical similarity search: type of search (Tanimoto, Tversky, Euclidian) search threshold (alpha, beta)
Chemical substructure search
Chemical structure exact search: options for tautomers, same skeleton in/excluding H, all isomers
Relevance score for each structure search result returned

15. Target API Methods

16. Target Info Data URIs (ConceptWiki, UniProt, ChEMBL, DrugBank)
Name, synonyms
Sequence, Protein existence, Mass, Functional annotation, GO terms, UniProt curated Protein-Protein Interactions, links to PDB and IntAct, Number of residues, Theoretical pI, Cellular location
ChEMBL target component description

17. Target Info Data Sources
ConceptWiki (including WikiPathways, Pathway Ontology concepts)
UniProt (including UniParc)
GOA (update Sept 9, 2013)
ChEMBL
target dataset triples
target component triples)
DrugBank
IntAct

18. Target Class Data Sources
GeneOntology Annotations (GOA): Classification of Targets
ChEMBL Targets: Classification of Targets
ENZYME: Classification of Targets

19. Target Pharmacology Data
Target data: Name, organism, target component, target type (API method for determining 16 different target types which can be used for filtering results)
Compound data: Activity (type, value, units, comment), pChEMBL, Assay (type, organism, description), URIs (OCRS, Chembl, ConceptWiki, DrugBank), Drug type, Generic name, SMILES, InChI, InChIKey, molecular weight, Rule of 5, Literature (DOI, PMID)

20. Target Class Pharmacology
Activity values for targets found in a given class in the supported hierarchies:
ENZYME Classification
ChEMBL Target Classification
GeneOntology

21. Pathway API Methods

22. Pathway Info Data URIs (WikiPathways, Pathway Ontology, ConceptWiki)
Title, Description, Annotations, Organism
Pathway participants
Compounds
Proteins
Literature

23. Pathway Info Data Sources
WikiPathways contains
Curated pathways, converted KEGG pathways
Metabolite identifiers: HMDB, ConceptWiki,
Target identifiers: GeneID, UniProt, ConceptWiki, Ensembl
Publication identifiers: DOI, PMID
NCBI taxonomy URIs and textual names

24. Open PHACTS API Methods for Hierarchies
1.3 release methods for hierarchies and classifications: ENZYME, GeneOntology, ChEBI, and ChEMBL targets

25. Hierarchy Methods
Visualization of hierarchy data by hierarchy structure:
ENZYME
ChEBI
ChEMBL target classification
GeneOntology

26. Basic hierarchy API methods
ENZYME EC EC
ChEMBL Target Hierarchy
(Root) EC EC EC EC
GeneOntology
Biological process
Molecular function
Cellular component
ChEBI
Subatomic
particle
Chemical entity
Has
role

27. Basic hierarchy API methods
DNA methylation
DNA methylation or demethylation
regulation of gene expression, epigenetic
DNA alkylation
macromolecule methylation
cellular response to hypoxia
regulation of transcription from RNA
polymerase II promoter in response to hypoxia
hypoxia-inducible factor-1alpha
signaling pathway

28. Query of ChEMBL Target Classification
ChEMBL Target Hierarchy Query for Protein Kinase class : CHEMBL_PC_320
646 Results
Transversal of all nodes below Protein Kinase to retrieve all leaves (targets), e.g all 3 proteins in the Histk node will be returned

29. Closer look: HistK class members
Query with classes:
Atypical: CHEMBL_PC_1451 or
Histk: CHEMBL_PC_267
Same 3 results for both classes:
2 different types of targets

30. “Protein family” target: PKC Alpha
Target Class Members List: Query for Alpha class CHEMBL_PC_317
PKC alpha (P17252) is part of protein family target, Chembl , which is comprised of members from several other PKC classes

31. Target Classification: PKC Alpha
Target Classification: Query for protein target PKC alpha (P17252)

32. Classification API for ChEMBL targets
A “protein family” target can be represented in several classes
P17252 is a “single protein” target as well as part of a “protein family” target
For retrieving only “single protein” targets, filter results by using the target_type restriction with the “single_protein” parameter
The Target Classification API method returns all classes that have been annotated to contain the target
P17252 as part of the “protein family” target is found in classes: Ser_Thr, Agc, Pkc, Alpha, as well as Camk and Pkd
P17252 as part of the “protein family” target is found in the ENZYME classes: EC and EC

33. Target Classification: GO terms
Target Classification method returns all GO classes that have been annotated to contain the target. Similar to ChEMBL, super classes are returned.

34. Query for protein target PKC alpha (P17252)
Classes of compounds that have pharmacology with a target: ChEBI results
Query for protein target PKC alpha (P17252)
Target query:
PKC Alpha
Compound class result:
monohydroxyquinoline

35. Members of ChEBI Compound Class: monohydroxyquinoline
Compound Class Members List: Query for monohydroxyquinoline (ChEBI_38775)
The members of the compound class of monohydroxyquinoline (indacaterol, chloroxine, etc) can be used In Compound Classifications methods

36. Compound Classification: Indacaterol
Compound Classification: Query for compound Indacaterol (OPS )
Concepts from the 3 branches of the ontology can be returned. Has role concepts: beta-adrenergic agonist and
bronchodilator agent
Chemical entity (type) concepts: quinoline

37. Hierarchical Activity Clustering Use Case
Sorafenib:
2755 Assay Points total
Activity only cutoff returned 707 results
Human only cutoff returned 634 results
Single Protein only cutoff returned 482 results
120 distinct human targets
But what does the distribution look like?
When you run pharmacology on a promiscuous compound you’re going to get hits to a lot of different targets-
You may want to cluster those hits by family, to see whether the hits were concentrated in sets of protein types-
This example starts the compound Sorafenib, and filters for human, activity type pharmacology, and single proteins only – which reduces the pool to120 distinct protein-compound links-

38. -Developed a small script, for each target, get the hierarchy [A => B => C] and set a counter for each level [A=1, B=1, C=1] Then, get the next protein hit, and get the full hierarchy: [A => B => D]  And set a counter for each level [A=2, B=2, C=1, D=1]-
-Results in “tree-node to count distinct target proteins"-
-Use the basic API functionality (Hierarchies: Parent nodes) for each node, to get the full path from tree top and concatenated it
Put path->count in excel and sorted-
Shows that the target proteins group on the two main kinase branches, and other specific nodes s such as Tie, Src, Eph where there are many hits.

39. Extra Methods Map URL: visualization of mappings between URLs
Data sources:
visualization of VoID for integrated data sources